def center_point1():
outdir = get_comptests_output_dir()
templates = load_tile_types()
for k, v in templates.items():
if isinstance(v, LaneSegment):
area = RectangularArea((-2, -2), (3, 3))
dest = os.path.join(outdir, k)
N = len(v.control_points)
betas = list(np.linspace(-2, N + 1, 20))
betas.extend(range(N))
betas = sorted(betas)
transforms = []
for timestamp in betas:
beta = timestamp
p = v.center_point(beta)
# print('%s: %s' % (beta, geo.SE2.friendly(p)))
transform = SE2Transform.from_SE2(p)
transforms.append(transform)
c = SampledSequence[SE2Transform](betas, transforms)
v.set_object("a", PlacedObject(), ground_truth=c)
draw_static(v, dest, area=area)
def svg2():
outdir = get_comptests_output_dir()
templates = load_tile_types()
for k, v in templates.items():
area = RectangularArea((-1, -1), (1, 1))
dest = os.path.join(outdir, k)
draw_static(v, dest, area=area)
def lane_pose_test1():
outdir = get_comptests_output_dir()
# load one of the maps (see the list using dt-world-draw-maps)
dw = load_map("udem1")
v = 5
# define a SampledSequence with timestamp, command
commands_sequence = SampledSequence.from_iterator(
[
# we set these velocities at 1.0
(1.0, WheelVelocityCommands(0.1 * v, 0.1 * v)),
# at 2.0 we switch and so on
(2.0, WheelVelocityCommands(0.1 * v, 0.4 * v)),
(4.0, WheelVelocityCommands(0.1 * v, 0.4 * v)),
(5.0, WheelVelocityCommands(0.1 * v, 0.2 * v)),
(6.0, WheelVelocityCommands(0.1 * v, 0.1 * v)),
]
)
# we upsample the sequence by 5
commands_sequence = commands_sequence.upsample(5)
## Simulate the dynamics of the vehicle
# start from q0
q0 = geo.SE2_from_translation_angle([1.8, 0.7], 0)
# instantiate the class that represents the dynamics
dynamics = reasonable_duckiebot()
# this function integrates the dynamics
poses_sequence = get_robot_trajectory(dynamics, q0, commands_sequence)
#################
# Visualization and rule evaluation
# Creates an object 'duckiebot'
ego_name = "duckiebot"
db = DB18() # class that gives the appearance
# convert from SE2 to SE2Transform representation
transforms_sequence = poses_sequence.transform_values(SE2Transform.from_SE2)
# puts the object in the world with a certain "ground_truth" constraint
dw.set_object(ego_name, db, ground_truth=transforms_sequence)
# Rule evaluation (do not touch)
interval = SampledSequence.from_iterator(enumerate(commands_sequence.timestamps))
evaluated = evaluate_rules(
poses_sequence=transforms_sequence,
interval=interval,
world=dw,
ego_name=ego_name,
)
timeseries = make_timeseries(evaluated)
# Drawing
area = RectangularArea((0, 0), (3, 3))
draw_static(dw, outdir, area=area, timeseries=timeseries)
def svg1():
outdir = get_comptests_output_dir()
control_points = [
SE2Transform.from_SE2(geo.SE2_from_translation_angle([0, 0], 0)),
SE2Transform.from_SE2(geo.SE2_from_translation_angle([1, 0], 0)),
SE2Transform.from_SE2(geo.SE2_from_translation_angle([2, -1], np.deg2rad(-90))),
]
width = 0.3
ls = LaneSegment(width, control_points)
area = RectangularArea((-1, -2), (3, 2))
draw_static(ls, outdir, area=area)
def lane_pose_test1():
outdir = get_comptests_output_dir()
dm = load_map('udem1')
print(get_object_tree(dm, attributes=True))
res = get_skeleton_graph(dm)
# area = RectangularArea((0, 0), (3, 3))
draw_static(res.root2, outdir + '/root2')
# draw_static(dm, outdir + '/orig')
print(get_object_tree(res.root2, attributes=True))
def lane_pose_segment1():
outdir = get_comptests_output_dir()
dm = load_map("udem1")
_ = get_object_tree(dm, attributes=True)
res = get_skeleton_graph(dm)
# area = RectangularArea((0, 0), (3, 3))
draw_static(res.root2, outdir + "/root2")
# draw_static(dm, outdir + '/orig')
_ = get_object_tree(res.root2, attributes=True)
def _eval_poses_sequence(self, poses_sequence, outdir=None):
"""
:param poses_sequence:
:param outdir: If None evaluation outputs plots won't be saved
:return:
"""
# puts the object in the world with a certain "ground_truth" constraint
self.dw.set_object(self.ego_name, self.db, ground_truth=poses_sequence)
# Rule evaluation (do not touch)
interval = SampledSequence.from_iterator(
enumerate(poses_sequence.timestamps))
evaluated = evaluate_rules(poses_sequence=poses_sequence,
interval=interval,
world=self.dw,
ego_name=self.ego_name)
if outdir is not None:
timeseries = make_timeseries(evaluated)
draw_static(self.dw, outdir, timeseries=timeseries)
print(self.dw.get_drawing_children())
self.dw.remove_object(self.ego_name)
self.dw.remove_object('visualization')
return evaluated
def check_car_dynamics_correct(klass, CarCommands, CarParams):
"""
:param klass: the implementation
:return:
"""
# load one of the maps (see the list using dt-world-draw-maps)
outdir = get_comptests_output_dir()
dw = load_map('udem1')
v = 5
# define a SampledSequence with timestamp, command
commands_sequence = SampledSequence.from_iterator([
# we set these velocities at 1.0
(1.0, CarCommands(0.1 * v, 0.1 * v)),
# at 2.0 we switch and so on
(2.0, CarCommands(0.1 * v, 0.4 * v)),
(4.0, CarCommands(0.1 * v, 0.4 * v)),
(5.0, CarCommands(0.1 * v, 0.2 * v)),
(6.0, CarCommands(0.1 * v, 0.1 * v)),
])
# we upsample the sequence by 5
commands_sequence = commands_sequence.upsample(5)
## Simulate the dynamics of the vehicle
# start from q0 and v0
q0 = geo.SE2_from_translation_angle([1.8, 0.7], 0)
v0 = geo.se2.zero()
c0 = q0, v0
# instantiate the class that represents the dynamics
dynamics = CarParams(10.0)
# this function integrates the dynamics
poses_sequence = get_robot_trajectory(dynamics, q0, commands_sequence)
#################
# Visualization and rule evaluation
# Creates an object 'duckiebot'
ego_name = 'duckiebot'
db = DB18() # class that gives the appearance
# convert from SE2 to SE2Transform representation
transforms_sequence = poses_sequence.transform_values(
SE2Transform.from_SE2)
# puts the object in the world with a certain "ground_truth" constraint
dw.set_object(ego_name, db, ground_truth=transforms_sequence)
# Rule evaluation (do not touch)
interval = SampledSequence.from_iterator(
enumerate(commands_sequence.timestamps))
evaluated = evaluate_rules(poses_sequence=transforms_sequence,
interval=interval,
world=dw,
ego_name=ego_name)
timeseries = make_timeseries(evaluated)
# Drawing
area = RectangularArea((0, 0), (3, 3))
draw_static(dw, outdir, area=area, timeseries=timeseries)
expected = {
1.0:
geo.SE2_from_translation_angle([1.8, 0.7], 0.0),
1.6:
geo.SE2_from_translation_angle([2.09998657, 0.70245831],
0.016389074695313716),
2.0:
geo.SE2_from_translation_angle([2.29993783, 0.70682836],
0.027315124492189525),
2.4:
geo.SE2_from_translation_angle([2.49991893, 0.70792121],
-0.016385672773040847),
2.8:
geo.SE2_from_translation_angle([2.69975684, 0.70027647],
-0.060086470038271216),
3.2:
geo.SE2_from_translation_angle([2.89906999, 0.68390873],
-0.10378726730350164),
3.6:
geo.SE2_from_translation_angle([3.09747779, 0.65884924],
-0.14748806456873198),
4.0:
geo.SE2_from_translation_angle([3.2946014, 0.62514586],
-0.19118886183396236),
4.6:
geo.SE2_from_translation_angle([3.58705642, 0.55852875],
-0.25674005773180786),
5.0:
geo.SE2_from_translation_angle([3.77932992, 0.50353298],
-0.3004408549970382),
6.0:
geo.SE2_from_translation_angle([4.2622088, 0.37429798],
-0.22257046876429318),
}
for t, expected_pose in expected.items():
assert np.allclose(poses_sequence.at(t=t), expected_pose), t
print('All tests passed successfully!')
